Journal of Integrative Bioinformatics最新文献

{"title":"Big data in the healthcare system: a synergy with artificial intelligence and blockchain technology.","authors":"Reyes-González Juan Pablo,&nbsp;Díaz-Peregrino Roberto,&nbsp;Soto-Ulloa Victor,&nbsp;Galvan-Remigio Isabel,&nbsp;Castillo Paul,&nbsp;Ogando-Rivas Elizabeth","doi":"10.1515/jib-2020-0035","DOIUrl":"https://doi.org/10.1515/jib-2020-0035","url":null,"abstract":"<p><p>In the last decades big data has facilitating and improving our daily duties in the medical research and clinical fields; the strategy to get to this point is understanding how to organize and analyze the data in order to accomplish the final goal that is improving healthcare system, in terms of cost and benefits, quality of life and outcome patient. The main objective of this review is to illustrate the state-of-art of big data in healthcare, its features and architecture. We also would like to demonstrate the different application and principal mechanisms of big data in the latest technologies known as blockchain and artificial intelligence, recognizing their benefits and limitations. Perhaps, medical education and digital anatomy are unexplored fields that might be profitable to investigate as we are proposing. The healthcare system can be revolutionized using these different technologies. Thus, we are explaining the basis of these systems focused to the medical arena in order to encourage medical doctors, nurses, biotechnologies and other healthcare professions to be involved and create a more efficient and efficacy system.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"19 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39326687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>In silico</i> gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment.","authors":"Mei Yen Man,&nbsp;Mohd Saberi Mohamad,&nbsp;Yee Wen Choon,&nbsp;Mohd Arfian Ismail","doi":"10.1515/jib-2020-0037","DOIUrl":"https://doi.org/10.1515/jib-2020-0037","url":null,"abstract":"<p><p>Microorganisms commonly produce many high-demand industrial products like fuels, food, vitamins, and other chemicals. Microbial strains are the strains of microorganisms, which can be optimized to improve their technological properties through metabolic engineering. Metabolic engineering is the process of overcoming cellular regulation in order to achieve a desired product or to generate a new product that the host cells do not usually need to produce. The prediction of genetic manipulations such as gene knockout is part of metabolic engineering. Gene knockout can be used to optimize the microbial strains, such as to maximize the production rate of chemicals of interest. Metabolic and genetic engineering is important in producing the chemicals of interest as, without them, the product yields of many microorganisms are normally low. As a result, the aim of this paper is to propose a combination of the Bat algorithm and the minimization of metabolic adjustment (BATMOMA) to predict which genes to knock out in order to increase the succinate and lactate production rates in <i>Escherichia coli</i> (<i>E. coli</i>).</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 3","pages":""},"PeriodicalIF":1.9,"publicationDate":"2021-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39277083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the border of the amyloidogenic sequences: prefix analysis of the parallel beta sheets in the PDB_Amyloid collection.","authors":"Kristóf Takács,&nbsp;Vince Grolmusz","doi":"10.1515/jib-2020-0043","DOIUrl":"https://doi.org/10.1515/jib-2020-0043","url":null,"abstract":"<p><p>The Protein Data Bank (PDB) today contains more than 174,000 entries with the 3-dimensional structures of biological macromolecules. Using the rich resources of this repository, it is possible identifying subsets with specific, interesting properties for different applications. Our research group prepared an automatically updated list of amyloid- and probably amyloidogenic molecules, the PDB_Amyloid collection, which is freely available at the address http://pitgroup.org/amyloid. This resource applies exclusively the geometric properties of the steric structures for identifying amyloids. In the present contribution, we analyze the starting (i.e., prefix) subsequences of the characteristic, parallel beta-sheets of the structures in the PDB_Amyloid collection, and identify further appearances of these length-5 prefix subsequences in the whole PDB data set. We have identified this way numerous proteins, whose normal or irregular functions involve amyloid formation, structural misfolding, or anti-coagulant properties, simply by containing these prefixes: including the T-cell receptor (TCR), bound with the major histocompatibility complexes MHC-1 and MHC-2; the p53 tumor suppressor protein; a mycobacterial RNA polymerase transcription initialization complex; the human bridging integrator protein BIN-1; and the tick anti-coagulant peptide TAP.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"19 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jib-2020-0043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39217075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthetic biology open language visual (SBOL Visual) version 2.3.","authors":"Hasan Baig,&nbsp;Pedro Fontanarossa,&nbsp;Vishwesh Kulkarni,&nbsp;James McLaughlin,&nbsp;Prashant Vaidyanathan,&nbsp;Bryan Bartley,&nbsp;Shyam Bhakta,&nbsp;Swapnil Bhatia,&nbsp;Mike Bissell,&nbsp;Kevin Clancy,&nbsp;Robert Sidney Cox,&nbsp;Angel Goñi Moreno,&nbsp;Thomas Gorochowski,&nbsp;Raik Grunberg,&nbsp;Jihwan Lee,&nbsp;Augustin Luna,&nbsp;Curtis Madsen,&nbsp;Goksel Misirli,&nbsp;Tramy Nguyen,&nbsp;Nicolas Le Novere,&nbsp;Zachary Palchick,&nbsp;Matthew Pocock,&nbsp;Nicholas Roehner,&nbsp;Herbert Sauro,&nbsp;James Scott-Brown,&nbsp;John T Sexton,&nbsp;Guy-Bart Stan,&nbsp;Jeffrey J Tabor,&nbsp;Logan Terry,&nbsp;Marta Vazquez Vilar,&nbsp;Christopher A Voigt,&nbsp;Anil Wipat,&nbsp;David Zong,&nbsp;Zach Zundel,&nbsp;Jacob Beal,&nbsp;Chris Myers","doi":"10.1515/jib-2020-0045","DOIUrl":"https://doi.org/10.1515/jib-2020-0045","url":null,"abstract":"<p><p>People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.3 of SBOL Visual, which builds on the prior SBOL Visual 2.2 in several ways. First, the specification now includes higher-level \"interactions with interactions,\" such as an inducer molecule stimulating a repression interaction. Second, binding with a nucleic acid backbone can be shown by overlapping glyphs, as with other molecular complexes. Finally, a new \"unspecified interaction\" glyph is added for visualizing interactions whose nature is unknown, the \"insulator\" glyph is deprecated in favor of a new \"inert DNA spacer\" glyph, and the polypeptide region glyph is recommended for showing 2A sequences.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 3","pages":""},"PeriodicalIF":1.9,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jib-2020-0045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39071280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploratory and discriminant analysis of plant phenolic profiles obtained by UV-vis scanning spectroscopy.","authors":"Monique Souza, Jucinei José Comin, Rodolfo Moresco, Marcelo Maraschin, Claudinei Kurtz, Paulo Emílio Lovato, Cledimar Rogério Lourenzi, Fernanda Kokowicz Pilatti, Arcângelo Loss, Shirley Kuhnen","doi":"10.1515/jib-2019-0056","DOIUrl":"10.1515/jib-2019-0056","url":null,"abstract":"<p><p>Some species of cover crops produce phenolic compounds with allelopathic potential. The use of math, statistical and computational tools to analyze data obtained with spectrophotometry can assist in the chemical profile discrimination to choose which species and cultivation are the best for weed management purposes. The aim of this study was to perform exploratory and discriminant analysis using R package specmine on the phenolic profile of <i>Secale cereale</i> L., <i>Avena strigosa</i> L. and <i>Raphanus sativus</i> L. shoots obtained by UV-vis scanning spectrophotometry. Plants were collected at 60, 80 and 100 days after sowing and at 15 and 30 days after rolling in experiment in Brazil. Exploratory and discriminant analysis, namely principal component analysis, hierarchical clustering analysis, <i>t</i>-test, fold-change, analysis of variance and supervised machine learning analysis were performed. Results showed a stronger tendency to cluster phenolic profiles according to plant species rather than crop management system, period of sampling or plant phenologic stage. PCA analysis showed a strong distinction of <i>S. cereale</i> L. and <i>A. strigosa</i> L. 30 days after rolling. Due to the fast analysis and friendly use, the R package specmine can be recommended as a supporting tool to exploratory and discriminatory analysis of multivariate data.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 3","pages":""},"PeriodicalIF":1.9,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38992260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural relation matching: an algorithm to identify structural patterns into RNAs and their interactions.","authors":"Michela Quadrini","doi":"10.1515/jib-2020-0039","DOIUrl":"https://doi.org/10.1515/jib-2020-0039","url":null,"abstract":"<p><p>RNA molecules play crucial roles in various biological processes. Their three-dimensional configurations determine the functions and, in turn, influences the interaction with other molecules. RNAs and their interaction structures, the so-called RNA-RNA interactions, can be abstracted in terms of secondary structures, i.e., a list of the nucleotide bases paired by hydrogen bonding within its nucleotide sequence. Each secondary structure, in turn, can be abstracted into cores and shadows. Both are determined by collapsing nucleotides and arcs properly. We formalize all of these abstractions as arc diagrams, whose arcs determine loops. A secondary structure, represented by an arc diagram, is pseudoknot-free if its arc diagram does not present any crossing among arcs otherwise, it is said pseudoknotted. In this study, we face the problem of identifying a given structural pattern into secondary structures or the associated cores or shadow of both RNAs and RNA-RNA interactions, characterized by arbitrary pseudoknots. These abstractions are mapped into a matrix, whose elements represent the relations among loops. Therefore, we face the problem of taking advantage of matrices and submatrices. The algorithms, implemented in Python, work in polynomial time. We test our approach on a set of 16S ribosomal RNAs with inhibitors of <i>Thermus thermophilus</i>, and we quantify the structural effect of the inhibitors.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 2","pages":"111-126"},"PeriodicalIF":1.9,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jib-2020-0039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39031294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-evaluation of social mining for classification of depressed online personas.","authors":"Alina Trifan,&nbsp;José Luis Oliveira","doi":"10.1515/jib-2020-0051","DOIUrl":"https://doi.org/10.1515/jib-2020-0051","url":null,"abstract":"<p><p>With the continuous increase in the use of social networks, social mining is steadily becoming a powerful component of digital phenotyping. In this paper we explore social mining for the classification of self-diagnosed depressed users of Reddit as social network. We conduct a cross evaluation study based on two public datasets in order to understand the impact of transfer learning when the data source is virtually the same. We further complement these results with an experiment of transfer learning in post-partum depression classification, using a corpus we have collected for the matter. Our findings show that transfer learning in social mining might still be at an early stage in computational research and we thoroughly discuss its implications.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 2","pages":"101-110"},"PeriodicalIF":1.9,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jib-2020-0051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39001347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiac well-being indexes: a decision support tool to monitor cardiovascular health.","authors":"Ana Duarte, Orlando Belo","doi":"10.1515/jib-2020-0040","DOIUrl":"10.1515/jib-2020-0040","url":null,"abstract":"<p><p>Despite the increasing awareness about its severity and the importance of adopting preventive habits, cardiovascular disease remains the leading cause of death worldwide. Most people already recognize that a healthy lifestyle, which includes a balanced diet and the practice of physical activity, is essential to prevent this disease. However, since few simple mechanisms allow a self-assessment and a continuous monitoring of the level of cardiac well-being, people are not conscious enough about their own cardiovascular health status. In this context, this paper presents and describes a tool related to the creation of cardiac well-being indexes that allow a quick and intuitive monitoring and visualization of the users' cardiovascular health level over time. For its implementation, data mining techniques were used to calculate the indexes, and a data warehouse was built to archive the data and to support the construction of dashboards for presenting the results.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 2","pages":"127-138"},"PeriodicalIF":1.5,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8238473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25520102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Super-rapid race for saving lives by developing COVID-19 vaccines.","authors":"Anusha Uttarilli,&nbsp;Sridhar Amalakanti,&nbsp;Phaneeswara-Rao Kommoju,&nbsp;Srihari Sharma,&nbsp;Pankaj Goyal,&nbsp;Gowrang Kasaba Manjunath,&nbsp;Vineet Upadhayay,&nbsp;Alisha Parveen,&nbsp;Ravi Tandon,&nbsp;Kumar Suranjit Prasad,&nbsp;Tikam Chand Dakal,&nbsp;Izhar Ben Shlomo,&nbsp;Malik Yousef,&nbsp;Muniasamy Neerathilingam,&nbsp;Abhishek Kumar","doi":"10.1515/jib-2021-0002","DOIUrl":"https://doi.org/10.1515/jib-2021-0002","url":null,"abstract":"<p><p>The pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected millions of people and claimed thousands of lives. Starting in China, it is arguably the most precipitous global health calamity of modern times. The entire world has rocked back to fight against the disease and the COVID-19 vaccine is the prime weapon. Even though the conventional vaccine development pipeline usually takes more than a decade, the escalating daily death rates due to COVID-19 infections have resulted in the development of fast-track strategies to bring in the vaccine under a year's time. Governments, companies, and universities have networked to pool resources and have come up with a number of vaccine candidates. Also, international consortia have emerged to address the distribution of successful candidates. Herein, we summarize these unprecedented developments in vaccine science and discuss the types of COVID-19 vaccines, their developmental strategies, and their roles as well as their limitations.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 1","pages":"27-43"},"PeriodicalIF":1.9,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jib-2021-0002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25525257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Special issue on COVID-19 data integration opportunities and vaccine development strategies.","authors":"Jens Allmer","doi":"10.1515/jib-2021-0006","DOIUrl":"https://doi.org/10.1515/jib-2021-0006","url":null,"abstract":"Viral infections affect a large part of the human population once or several times each year. Coronaviruses (CoV) are part of the viruses which cause ailments such as the common cold. With SARS-CoV-1, a dangerous variant of CoV caused an epidemic that did not spread worldwide (2002–2004). It has been contained with less than one thousand fatalities (WHO). Another beta coronavirus causing the middle east respiratory syndrome (MERS) broke out about a decade later (2013). While MERS cases are still present in 2021 (most cases reported by Saudi Arabia), the cumulative death toll is below one thousand despite a high case-to-fatality ratio of around 30% [1]. In 2019 SARS-CoV-2 caused a pandemic with abundant worldwide infections and about two million fatalities in early 2021 (http://covid19.who.int). With the SARS-CoV-2 pandemic active for more than one year, vaccines with emergency admittance are being delivered. Interestingly, during 50 years of research on vaccines against coronaviridae, such approaches are only now becoming available (Figure 1). Vaccination of a sufficiently large cohort of individuals to control the pandemic will take long at current vaccination rates. Therefore, it is essential to continue studying SARS-CoV-2 and try additional routes to prevent the virus’s spread or the disease. Yousef et al. state that testing data is fragmented and not readily available [2]. With a relatively large dataset provided by the Israeli government, they trained a machine-learning algorithm that aided in ranking symptoms, allowing testing prioritization. Demirci and Sacar Demirci show how post-transcriptional gene regulation can be involved in the COVID-19 disease and investigate different miRNAs’ targets and their differential expression [3]. Gültekin and Allmer show how novel information such as RNA binding potential and predicted CoV microRNAs could be incorporated into genome browsers [4]. Such data can help RNA-based drug design. Ahsan et al. tie together many resources with CoV’ information ranging from genomic data to clinical trials [5]. Due to the amount of data generated in the last year, such a resource was desperately needed. OverCOVID will help researchers to find the information they need and may enable integrative studies. Finally, Uttarilli et al. discuss the rapid development of COVID-19 vaccines [6]. Thus, this special issue brings together two applications of COVID-19 data, one visualization of such data, a resource potentially delivering data with integration potential, and a review of vaccine development, which could benefit from the resources mentioned above.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":"18 1","pages":"1-2"},"PeriodicalIF":1.9,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jib-2021-0006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25498300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}